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Plot 1

library(ggplot2)

aisc2024 <- read.csv("aisc.csv", header = TRUE)

aisc2024 |>                   # Start with the data
  ggplot(                     # Set up the plot.
    aes(
      x = tempo,
      y = arousal,
      size = instrumentalness,
      colour = danceability
    )
  ) +
  geom_point() +              # Scatter plot.
  geom_rug(linewidth = 0.1) + # Add 'fringes' to show data distribution.
  geom_text(                  # Add text labels from above.
    x = 121,
    y = 4.91,
    label = "Onda Corta - Sud America",
    size = 3,                 # Override size (not loudness here).
    hjust = "left",           # Align left side of label with the point.
    vjust = "center",         # Align vertical centre of label with the point.
    angle = 30                # Rotate the text label
  ) +
  scale_x_continuous(         # Fine-tune the x axis.
    limits = c(0, 200),
    breaks = c(50, 100, 150, 200), # Specify grid lines
    minor_breaks = NULL       # Remove 'minor' grid lines.
  ) +
  scale_y_continuous(         # Fine-tune the y axis in the same way.
    limits = c(1, 9),
    breaks = c(1, 5, 9),
    minor_breaks = NULL
  ) +
  scale_colour_viridis_c() +  # Use the popular viridis colour palette.
  scale_size_continuous(      # Fine-tune the sizes of each point.
    trans = "exp",            # Use an exp transformation to emphasise loud..
    guide = "none"            # Remove the legend for size.
  ) +
  theme_light() +             # Use a simpler theme.
  labs(                       # Make the titles nice.
    x = "Tempo",
    y = "Arousal",
    colour = "Danceability"
  )

test

Plot 2

aisc2024
                        artist                          title danceability
1                      Yapzech             We Are Stepping In    0.6339566
2                      HEL9000                   binary-b1o0d    0.4310685
3                     Yun+More                   Do AIs Dream    0.3005951
4                     Emo Hues                  Moonlit Tears    0.4309452
5                 Almost Human                      Yesterday    0.8798282
6             KicKRaTT KaOzBrD                       ARBOREAL    0.8517656
7             Ceremony Shadows                        Sunfall    0.5178320
8                    Vonpsyche                     The Nature    0.2069548
9                   Onda Corta                    Sud America    0.5871841
10                    swansong                 Ochiai Toshiya    0.7484748
11              PHANTOMSCHMERZ                Tanz Mit Der KI    0.3957726
12                      TIKHET                All Machineries    0.7838064
13                    Error305                Heart Not Found    0.3544357
14             CracksInTheReal               Petrushka Rising    0.7255723
15         Forest Little Music           The Laziness Complex    0.4532424
16           Robots Make Music                       Whatever    0.5141004
17                      Seva M          Defy the Odds (Again)    0.7134851
18                  mFriendOB3                  Danish Vanish    0.4082446
19 Asian Culture Research Team                    Overfitting    0.5775374
20                        KeRa Echoes Of The Synthetic Forest    0.5627679
21                    Dadabots                   Genre Cannon    0.6419406
22                  Pol Wagner                      Awakening    0.7298880
23                      Ziinan                  Signal Voyage    0.7222863
24                  StriderQED                    Inspiration    0.7432976
25                       ETFM                          Wakeup    0.6344830
26                    GANTASMO                   Natures Tomb    0.3984531
27                     Botuoso                     RabbitHole    0.6971996
28        The Grand Wamenawers                          Toxic    0.8210198
29                The Rockbots                Generative Love    0.4475500
30                   Genealogy                         Lalala    0.4659576
31                    DJ Swami                     One Mantra    0.5641023
32               Jenny Perelli                     Lets Fight    0.3156697
    valence  arousal instrumentalness tempo
1  4.252057 4.446585        0.8116079   121
2  3.764513 4.892605        0.6605874   155
3  3.587308 3.730796        0.8866421   154
4  3.509241 4.716523        0.5294363   118
5  3.630578 3.972751        0.8130572   154
6  3.759634 4.533846        0.5345818   116
7  3.546809 4.202670        0.5868522   154
8  3.537997 4.088050        0.5475702   154
9  3.754198 4.914463        0.3986959   121
10 3.427669 4.060219        0.4817626   116
11 3.289894 4.116500        0.6334715    75
12 3.271581 4.107907        0.6224679    64
13 3.822791 4.858078        0.4049374    75
14 3.394381 4.079172        0.6595098    85
15 3.884343 3.755157        0.9040143   154
16 3.910835 4.688392        0.5422015    87
17 4.172775 4.762912        0.4416753    97
18 3.640845 4.221984        0.5574242    75
19 3.706505 4.273816        0.6660838   121
20 3.351331 4.095325        0.7273520   154
21 3.972117 4.623346        0.7339450   140
22 3.692147 4.557771        0.5190139    80
23 4.330293 4.568987        0.7440484   138
24 4.276304 4.593785        0.5234275    67
25 4.164796 4.377752        0.7963970   116
26 3.340126 4.012445        0.5803508    90
27 3.268177 4.031115        0.5864089    77
28 4.210932 4.479538        0.6482085    63
29 4.135867 4.898949        0.3695597    75
30 3.689864 4.714108        0.6154362   121
31 3.021905 3.790338        0.6847970   154
32 3.653926 4.386634        0.5916983   132

test

Note that the echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot.